Text Generation
Transformers
PyTorch
TensorBoard
Safetensors
llama
Generated from Trainer
text-generation-inference
Instructions to use flytech/devchat-llama-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flytech/devchat-llama-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="flytech/devchat-llama-7b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("flytech/devchat-llama-7b") model = AutoModelForCausalLM.from_pretrained("flytech/devchat-llama-7b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use flytech/devchat-llama-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "flytech/devchat-llama-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "flytech/devchat-llama-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/flytech/devchat-llama-7b
- SGLang
How to use flytech/devchat-llama-7b with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "flytech/devchat-llama-7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "flytech/devchat-llama-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "flytech/devchat-llama-7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "flytech/devchat-llama-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use flytech/devchat-llama-7b with Docker Model Runner:
docker model run hf.co/flytech/devchat-llama-7b
sirr commited on
Commit ·
83649e4
1
Parent(s): 81b57fe
Upload LlamaForCausalLM
Browse files- config.json +2 -2
- generation_config.json +1 -1
- pytorch_model.bin +3 -0
config.json
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{
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"_name_or_path": "openlm-research/
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"architectures": [
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"LlamaForCausalLM"
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.33.
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"use_cache": true,
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"vocab_size": 32000
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}
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{
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"_name_or_path": "openlm-research/open_llama_7b_v2",
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"architectures": [
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"LlamaForCausalLM"
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],
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.33.1",
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"use_cache": true,
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"vocab_size": 32000
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}
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generation_config.json
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 0,
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"transformers_version": "4.33.
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}
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 0,
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"transformers_version": "4.33.1"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:a58b3ae1030cefb41c0bf759170dcc4ceeb5df199f4608e6b7a3a33eb75503ce
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size 1071707498
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